code: def __retrieve_with_progress(source: str, filename: str):
      """
      Downloads source to destination
      Displays progress bar
      Args:
          source: url of resource
          destination: local filepath
      Returns:
      """
      with open(filename, "wb") as f:
          response = urllib.request.urlopen(source)
          total = response.length
  
          if total is None:
              f.write(response.content)
          else:
              with tqdm(
                  total=total,
                  unit="B",
                  unit_scale=True,
                  unit_divisor=1024,
              ) as pbar:
                  for data in response:
                      f.write(data)
                      pbar.update(len(data))
  
file_path: NeMo/scripts/dataset_processing/speaker_tasks/get_hi-mia_data.py
imports: import argparse
  import json
  import logging
  import os
  import tarfile
  import urllib.request
  from glob import glob
  import librosa
  from sklearn.model_selection import StratifiedShuffleSplit
  from tqdm import tqdm
label_desc: Use image node_id 1 for calling a global function with example usage: __retrieve_with_progress(source, filename) without return types